Improved Particle Swarm Algorithm for Sparse Array with Superior Global Sidelobe Levels

In order to solve the challenge of sparse array optimization to achieve the global optimal peak sidelobe level, an improved particle swarm optimization algorithm is introduced. This method is used to optimize a sparse array consisting of 60 antennas and 86 half-wavelength apertures. The simulation results show that compared with the traditional particle swarm optimization and simulated annealing algorithms, the improved particle swarm optimization algorithm has excellent performance in coping with the challenge of sparse array optimization.